smallcorgi/Faster-RCNN_TF

Health v2 · maintenance only

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2342 stars · 1091 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A TensorFlow implementation of Faster R-CNN, a convolutional neural network for object detection with a region proposal network. It includes a demo with a pre-trained VGG16 model on PASCAL VOC 2007 and scripts for training on custom datasets.

Use cases

• run object detection on images with a pre-trained Faster R-CNN model
• train a Faster R-CNN detector on PASCAL VOC 2007
• reproduce Faster R-CNN research results in TensorFlow
• study a reference implementation of region proposal networks
• fine-tune a VGG16-based detector for custom object classes

When to choose

• you need a TensorFlow-based Faster R-CNN implementation for object detection research
• you want to train or evaluate on PASCAL VOC with a VGG16 backbone
• you need a lightweight detector that fits in 3GB of GPU memory
• you want readable code to learn how Faster R-CNN works internally

When to avoid

• you need state-of-the-art detection accuracy or modern architectures like DETR or YOLO
• you require active maintenance, recent TensorFlow 2.x support, or long-term updates
• you need production-ready deployment tooling or model export pipelines
• you want a simple high-level API rather than a research codebase

Facets

library · maturity maintenance

machine-learning deep-learning computer-vision image-processing computer-vision deep-learning machine-learning image-processing python cross-platform object-detection faster-rcnn tensorflow region-proposal-network vgg16 pascal-voc convnet research-code cython opencv gpu linux

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markdown · JSON · MCP: product_card(name="smallcorgi/Faster-RCNN_TF")